T-RO publishes fundamental papers on all aspects of robotics, featuring interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, and other fields. Robots and intelligent machines and systems are critical in areas such as industrial applications; service and personal assistants; surgical operations; space, underwater, and remote exploration; entertainment; safety, search, and rescue; military applications; agriculture applications; and intelligent vehicles. Special emphasis is placed on intelligent machines and systems for unstructured environments, where a significant portion of the environment is unknown and cannot be directly sensed or controlled. 

Examples of topics that fall within the scope of T-RO include:

    Design: mechanisms and actuation; robots with flexible elements; limbed structures; parallel and hybrid mechanisms; robot hands; snake-like and continuum robots; soft robots; modular robots; biomimetic and bioinspired robots; wheeled robots; underwater robots; flying robots; micro/nano robots; performance evaluation and optimization; modeling, identification, calibration
    Sensing and Perception: foundations of sensing and estimation; force and tactile sensing; range, sonar, and inertial Sensing; GPS and odometry; 3-D vision; object recognition; visual servoing; multisensor data fusion
    Manipulation, Interfaces, and Programming: motion and force planning and control for manipulation tasks; contact modeling and manipulation; grasping; cooperative manipulation; mobility and manipulation; haptics; active manipulation for perception; telerobotics; networked robots; robotic systems architectures and programming
    Moving in the Environment: world modelling; simultaneous localization and mapping (SLAM); motion planning and obstacle avoidance; modelling and control of legged robots, wheeled mobile robots, robots on rough terrain, underwater robots, aerial robots, and multiple mobile robot systems
    Robots at Work: industrial robotics; space robotics; robotics in agriculture and forestry; robotics in construction; robotics in hazardous applications; robotics in mining; search and rescue robotics; robot surveillance and security; intelligent vehicles; medical robotics and computer-integrated surgery; rehabilitation and healthcare robotics; domestic robotics
    Robots and Humans: humanoids; physical and cognitive human-robot interaction; human-robot augmentation; social and socially assistive robotics; learning from humans; behavior-based systems; AI reasoning methods for robotics; biologically-inspired robotics; evolutionary robotics; neurorobotics; perceptual robotics; roboethics

Papers describing specific current (industrial and beyond) applications are encouraged, provided that the paper convincingly demonstrates that it represents the best current practice, detailed characteristics and performance are included, and it is of general interest.

Special Issue on Visual SLAM
提出日: 2024-12-15

Important Dates
● Submissions open: June 15, 2024
● Submissions close: December 15, 2024
● Expected publication date: 2025

Guest Editors
Giovanni Cioffi, University of Zurich, Switzerland
Davide Scaramuzza, University of Zurich, Switzerland
Stefan Leutenegger, Technical University of Munich, Germany
Abhinav Valada, University of Freiburg, Germany
Teresa Vidal-Calleja, University of Technology Sydney, Australia
Guoquan (Paul) Huang, University of Delaware, USA

Overseeing Editor
Javier Civera, University of Zaragoza, Spain
 
Aims and Scope

The field of Visual SLAM (Simultaneous Localization And Mapping) has progressed
substantially since the last IEEE Transactions on Robotics special collection in 2008. Visual SLAM has attained a
consolidated level of maturity, finding applications in smartphones, AR/VR devices, and mobile
robots. Despite this progress, many questions remain open, such as: Are current methodologies
robust enough to handle outliers in data association effectively? Should the focus be on
learning-based end-to-end approaches, classical methodologies, or hybrid strategies? What is
the optimal map representation? 3D maps, NERF, Gaussian Splatting, or alternatives? Can
Visual SLAM leverage recent breakthroughs in Large Language Models and Foundation Models
to enhance its capabilities?

This special collection invites contributions from researchers to present their latest
advancements, propose solutions to open challenges and outline new avenues for research
within the realm of Visual SLAM.

We encourage submissions related, but not limited, to the following topics:

● Robust SLAM
● Representations in SLAM (NeRF, Gaussian Splatting, etc.)
● Semantic, Object-level, and Dynamic SLAM
● Large Scale SLAM
● Unconventional vision sensors for SLAM (event cameras, thermal cameras)
● SLAM for Robotics Navigation
● Multi-agents SLAM
● Visual(-Inertial) Odometry
● Learning-based SLAM
● Beyond Conventional SLAM (Large Language Models, Foundation Models, …)

We welcome top-quality original (unpublished) articles and review papers, following the IEEE
T-RO journal instructions for authors. Each submission will be peer-reviewed and the selection
of papers will be based on their originality, impact, and relevance to the scope of the special
collection. To ensure that all manuscripts are correctly identified for evaluation for the special
section, please select “Visual SLAM” in the submission process.